Estimation of spatial and/or temporal variation in soil moisture is typically an important parameter in a number of applications ranging from efficiency of agricultural practices, to estimation of recharge to groundwater systems for modeling studies, to estimation of slope stabilities following precipitation, to monitoring the impact of mining operations. Such variation can be related to a number of interacting processes including heterogeneity of the sediments, spatial variation in recharge (related to spatial variation in precipitation, leaks in surface or buried pipelines, and vegetation), and spatial variation in evapotranspiration. Measurement of soil moisture is therefore an important challenge in a number of modeling and field optimization processes; a challenge which has attracted attention from the early days of technical research on the vadose zone to a plethora of journal articles focused on this soil property.
A number of methods have been developed to measure soil moisture either locally (e.g., at the meter scale or smaller) through direct or indirect measures on local sediments or at larger scales (10's of meters to watershed scale) through remote imaging. Briefly, local measures have been based predominantly on capacitance or resistance measures in soils, including time domain reflectometry (TDR), frequency domain reflectometry (FDR), and soil block measurements. To a lesser degree, soil tensiometers have been used to measure pore water pressure and this pressure has, through calibration of the pressure-moisture relationship, been related to soil moisture. These tools provide for measuring soil moisture at short time intervals with a support volume of the measurement on the order of the probe (e.g., soil blocks) to several multiples of the size of the probe (e.g., TDR and FDR) used in the measurement. As such, relatively precise measurement can be made, but field scale characterization of the spatial distribution of soil moisture would require a large number of probes.
In contrast, a number of imaging methods have been applied to measurement of the spatial distribution of soil moisture at scales ranging from agricultural fields to watersheds. Principal among these in the recent literature have been satellite imagery, thermal inertia methods, and assimilation of microwave signals. These methods have generally provided the ability to monitor the spatial distribution of soil moisture, but are limited spatially and temporally to locations where remotely sensed images are available (particularly for the satellite and temperature methods). Further, the spatial resolution is typically constrained by available storage/pixel dimensions.
Comparison of these two ranges of instruments (local versus large-scale) provides insight into a portion of the difficulty in integrating data over multiple scales of characterization with modeling efforts. Hence, the potential of remote measurement of soil moisture using available WLAN signals provides multiple advantages, including extremely low cost measurement with almost ubiquitous coverage in populated regions. Further, in light of the discussion above, WLAN networks also provide the promise of providing estimates of soil moisture over different averaging areas (averaging volumes) through judicious selection of beacon and receiver locations.
To date, radio frequency (RF) characterization of soil moisture has largely been associated with large-area characterizations using aerial reconnaissance and/or satellite observations. These approaches are constrained by limited earth coverage, low revisit times, and high cost, and do not offer flexibility to achieve customized monitoring architectures for smaller-scale applications. As one illustration, the Soil Moisture Active Passive (SMAP) Mission sensor estimates soil moisture at resolutions of 10 km with revisit intervals of 2 to 3 days. Such spatial and temporal resolutions are not well suited to address soil-moisture monitoring in low-cost field-scale applications requiring high revisit rates. Some experimentation has been performed using either active or passive ground-based RF systems. Active ground-based systems, mainly SAR systems, have been used for radar imaging of terrain and other applications including interferometric monitoring of large man-made structures. Most of the experimental systems described in literature are active systems with a Vector Network Analyzer (VNA) to perform a stepped frequency construction of a wide-band signal for high range resolution. Among the ground-based passive systems, a microwave radiometer has been used to infer soil moisture from polarization component magnitudes using non-coherent detection of ambient reflected microwaves over small areas for assimilation into precipitation models. A different passive ground based sensing approach employs an in-situ GPS receiver for near surface soil measurements. This sensing method exploits signals from the GPS constellation and measures SNR variations induced by satellite motion to infer soil moisture levels through subsequent model simulation. The technique reportedly offers resolutions on the order of 300 square meters, but the technique requires an in-situ receiver, relies on approximately 45 minutes of satellite motion to generate a useful output, assumes a single dominant multipath component and knowledge of various environmental parameters, and suffers from a relative lack of control over the transmitter/receiver geometry and corresponding sensing resolution.
The goal of known irrigation management techniques is to achieve an optimum water supply for crop productivity. Escalating worldwide water shortages and irrigation costs have resulted in an increasing emphasis on developing irrigation techniques that minimize water use while maintaining productivity (i.e. maximize water use efficiency). Irrigation scheduling techniques that are based on plant or soil water status can help achieve this goal. The advantage of soil moisture measurements over plant water status is that soil moisture measurements can be used to determine the amount of water that needs to be applied, while plant measurements merely indicate when water is needed, but not how much. In addition, soil moisture measurements can be easily integrated into automated systems. Conventional soil moisture monitoring techniques such as dielectric or resistance measurements in soils can be unwieldy in field-scale applications due to the need for contact with the soil and the large number of sensors required for suitable coverage.
Remote sensing approaches have advantages because of their capacity to integrate over large areas. Technologies such as aerial reconnaissance and/or satellite observations are widely used for large-area characterizations. However, these approaches are oftentimes constrained by limited earth coverage, low revisit times, low resolution, high cost, and do not offer flexibility to achieve customized monitoring for variable-scale applications.